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+++ b/R/amaretto_vizualize.R
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+#' AMARETTO_VisualizeModule
+#'
+#' Function to visualize the gene modules
+#'
+#' @param AMARETTOinit List output from AMARETTO_Initialize().
+#' @param AMARETTOresults List output from AMARETTO_Run().
+#' @param ProcessedData List of processed input data
+#' @param ModuleNr Module number to visualize
+#' @param SAMPLE_annotation Matrix or Dataframe with sample annotation
+#' @param ID Column used as sample name
+#' @param show_row_names If TRUE, row names will be shown on the plot.
+#' @param order_samples Order samples in heatmap by mean or by clustering
+#'
+#' @importFrom circlize colorRamp2  rand_color
+#' @importFrom grid gpar unit
+#' @importFrom stats dist hclust
+#' @importFrom dplyr  left_join mutate  select  summarise  rename  filter case_when
+#' @import grDevices
+#' @import methods
+#' @importFrom ComplexHeatmap  HeatmapAnnotation Heatmap draw
+#' @importFrom tibble column_to_rownames  rownames_to_column
+#' @return result
+#' @export
+#'
+#' @examples
+#' data('ProcessedDataLIHC')
+#' AMARETTOinit <- AMARETTO_Initialize(ProcessedData = ProcessedDataLIHC,
+#'                                     NrModules = 2, VarPercentage = 50)
+#'
+#' AMARETTOresults <- AMARETTO_Run(AMARETTOinit)
+#'
+#' AMARETTO_VisualizeModule(AMARETTOinit = AMARETTOinit,AMARETTOresults = AMARETTOresults,
+#'                          ProcessedData = ProcessedDataLIHC, ModuleNr = 1)
+AMARETTO_VisualizeModule <- function(AMARETTOinit,AMARETTOresults,ProcessedData,ModuleNr,show_row_names=FALSE, SAMPLE_annotation=NULL,ID=NULL,order_samples=NULL) {
+  CNV_matrix <- ProcessedData[[2]]
+  MET_matrix <- ProcessedData[[3]]
+  CNVMet_Alterations <- DriversList_Alterations <- MET <- HGNC_symbol <- CNV <- NULL
+  if (ModuleNr>AMARETTOresults$NrModules){
+    stop('\tCannot plot Module',ModuleNr,' since the total number of modules is',AMARETTOresults$N,'.\n')
+  }
+  ModuleData<-as.data.frame(AMARETTOinit$MA_matrix_Var)[AMARETTOresults$ModuleMembership==ModuleNr,]
+  ModuleRegulators <- AMARETTOresults$AllRegulators[which(AMARETTOresults$RegulatoryPrograms[ModuleNr,] != 0)]
+  RegulatorData <- as.data.frame(AMARETTOinit$RegulatorData)[ModuleRegulators,]
+  ModuleGenes <- rownames(ModuleData)
+  cat('Module',ModuleNr,'has',length(rownames(ModuleData)),'genes and',length(ModuleRegulators),'regulators for',length(colnames(ModuleData)),'samples.\n')
+  Alterations<- tibble::rownames_to_column(as.data.frame(AMARETTOinit$RegulatorAlterations$Summary),"HGNC_symbol") %>% dplyr::rename(DriverList="Driver List") %>% dplyr::filter(HGNC_symbol %in% ModuleRegulators)
+  Alterations<- Alterations %>% dplyr::mutate(CNVMet_Alterations=case_when(MET==1 & CNV==1~"Methylation and copy number alterations",
+                                                                           CNV==1~"Copy number alterations",
+                                                                           MET==1~"Methylation aberrations",
+                                                                           MET==0 & CNV==0 ~"Not Altered"),
+                                              DriversList_Alterations=case_when(DriverList==0~"Driver not predefined",
+                                                                                DriverList==1~"Driver predefined"))
+
+  ha_drivers <- ComplexHeatmap::HeatmapAnnotation(df = tibble::column_to_rownames(Alterations,"HGNC_symbol") %>% dplyr::select(CNVMet_Alterations,DriversList_Alterations), col = list(CNVMet_Alterations= c("Copy number alterations"="#eca400","Methylation aberrations"="#006992","Methylation and copy number alterations"="#d95d39","Not Altered"="lightgray"),DriversList_Alterations=c("Driver not predefined"="lightgray","Driver predefined"="#588B5B")),which = "column", height = grid::unit(0.3, "cm"),name="",
+                                  annotation_legend_param = list(title_gp = grid::gpar(fontsize = 8),labels_gp = grid::gpar(fontsize = 6)))
+
+  overlapping_samples <- colnames(ModuleData)
+  
+  # Add NAs for Gene Expression samples not existing in CNV or MET data 
+
+  if (!is.null(CNV_matrix)){
+    non_CNV_sample_names<- overlapping_samples[!overlapping_samples%in%colnames(CNV_matrix)]
+    print(non_CNV_sample_names)
+    print(nrow(CNV_matrix))
+    print(length(non_CNV_sample_names))
+    CNV_extension_mat<- matrix(data=NA,nrow=nrow(CNV_matrix),ncol=length(non_CNV_sample_names))
+    colnames(CNV_extension_mat)<-non_CNV_sample_names
+    CNV_matrix<-cbind(CNV_matrix,CNV_extension_mat)
+  }
+  if (!is.null(MET_matrix)){
+    non_MET_sample_names<- overlapping_samples[!overlapping_samples%in%colnames(MET_matrix)]
+    MET_extension_mat<- matrix(data=NA,nrow=nrow(MET_matrix),ncol=length(non_MET_sample_names))
+    colnames(MET_extension_mat)<-non_MET_sample_names
+    MET_matrix<-cbind(MET_matrix,MET_extension_mat)
+  }
+
+  if(is.null(order_samples)){
+    overlapping_samples_clust<-overlapping_samples[order(colMeans(ModuleData[,overlapping_samples]))]
+  }else if(order_samples=="clust"){
+    SampleClustering<-stats::hclust(stats::dist(t(ModuleData[,overlapping_samples])), method = "complete", members = NULL)
+    overlapping_samples_clust<-overlapping_samples[SampleClustering$order]
+  }else {
+    print("ordering type not recognized, samples will be orderd based on mean expression of the module genes")
+    overlapping_samples_clust<-overlapping_samples[order(colMeans(ModuleData[,overlapping_samples]))]
+  }
+
+  ClustRegulatorData <- t(RegulatorData[,overlapping_samples_clust])
+  ClustModuleData <- t(ModuleData[,overlapping_samples_clust])
+  
+  if(length(ClustModuleData)<50){
+    fontsizeMo=6
+  } else if (length(ClustModuleData)<200){
+    fontsizeMo=4
+  } else {fontsizeMo=2}
+  
+  Regwidth <- ncol(ClustRegulatorData)*0.5
+  ha_Reg <- Heatmap(ClustRegulatorData, name = "Gene Expression", column_title = "Regulator Genes\nExpression",cluster_rows=FALSE,cluster_columns=TRUE,show_column_dend=FALSE,show_column_names=TRUE,show_row_names=FALSE,column_names_gp = grid::gpar(fontsize = fontsizeMo),top_annotation = ha_drivers,
+                    column_title_gp = grid::gpar(fontsize = 6, fontface = "bold"), col=circlize::colorRamp2(c(-max(abs(ClustRegulatorData)), 0, max(abs(ClustRegulatorData))), c("darkblue", "white", "darkred")),heatmap_legend_param = list(color_bar = "continuous",legend_direction = "horizontal",title_gp = grid::gpar(fontsize = 8),labels_gp = grid::gpar(fontsize = 6)), width = grid::unit(Regwidth, "cm"))
+
+
+  ha_Module <- Heatmap(ClustModuleData, name = " ", column_title = "Target Genes\nExpression",cluster_rows=FALSE,cluster_columns=TRUE,show_column_dend=FALSE,show_column_names=TRUE,show_row_names=show_row_names,column_names_gp = grid::gpar(fontsize = fontsizeMo),show_heatmap_legend = FALSE,
+                       column_title_gp = grid::gpar(fontsize = 6, fontface = "bold"), col=circlize::colorRamp2(c(-max(abs(ClustModuleData)), 0, max(abs(ClustModuleData))), c("darkblue", "white", "darkred")),heatmap_legend_param = list(color_bar = "continuous",legend_direction = "horizontal",title_gp = grid::gpar(fontsize = 8),labels_gp = grid::gpar(fontsize = 6)))
+
+  ha_list<- ha_Reg + ha_Module
+  if (!is.null(MET_matrix)){
+    METreg <- intersect(rownames(AMARETTOinit$RegulatorAlterations$MET),ModuleRegulators)
+    print("MET regulators will be included when available")
+    if (length(METreg)>0){
+      MET_matrix = as.data.frame(MET_matrix)
+      METData2 = METData = as.matrix(MET_matrix[unlist(Alterations %>% dplyr::filter(MET==1) %>% dplyr::select(HGNC_symbol)),overlapping_samples_clust])
+      METData2[which(METData>0)] <- "Hyper-methylated"  # hyper
+      METData2[which(METData<0)] <- "Hypo-methylated"  # hypo
+      METData2[which(METData==0)] <- "Not altered" # nothing
+      METData2<-t(METData2)
+      Metwidth=ncol(METData2)*0.7
+      Met_col=structure(c("#006992","#d95d39","white"),names=c("Hyper-methylated","Hypo-methylated","Not altered"))
+      ha_Met <- Heatmap(METData2, name = "Methylation State", column_title = "Methylation", cluster_rows=FALSE,cluster_columns=TRUE,show_column_dend=FALSE,show_column_names=TRUE,show_row_names=FALSE,column_names_gp = grid::gpar(fontsize = 6),show_heatmap_legend = TRUE,
+                        column_title_gp = gpar(fontsize = 6, fontface = "bold"), col = Met_col, width = grid::unit(Metwidth, "cm"),heatmap_legend_param = list(title_gp = gpar(fontsize = 8),labels_gp = grid::gpar(fontsize = 6)))
+      ha_list<- ha_Met + ha_list
+    }
+  }
+
+  if (!is.null(CNV_matrix)){
+    CNVreg <- intersect(rownames(AMARETTOinit$RegulatorAlterations$CNV),ModuleRegulators)
+    print("CNV regulators will be included when available")
+    if (length(CNVreg)>0){
+      CNV_matrix = as.data.frame(CNV_matrix)
+      CNVData2 = CNVData = as.matrix(CNV_matrix[unlist(Alterations %>% dplyr::filter(CNV==1) %>% dplyr::select(HGNC_symbol)),overlapping_samples_clust])
+      CNVData2[which(CNVData>=0.1)] <- "Amplified"  # amplification
+      CNVData2[which(CNVData<=(-0.1))] <- "Deleted"  # deletion
+      CNVData2[which(CNVData<0.1 & CNVData>(-0.1))] <- "Not altered" # nothing
+      CNVData2<-t(CNVData2)
+      CNVwidth=ncol(CNVData2)*0.7
+      CNV_col=structure(c("#006992","#d95d39","white"),names=c("Deleted","Amplified","Not altered"))
+      ha_CNV <- Heatmap(CNVData2, name = "CNV State", column_title = "CNV", cluster_rows=FALSE,cluster_columns=TRUE,show_column_dend=FALSE,show_column_names=TRUE,show_row_names=FALSE,column_names_gp = grid::gpar(fontsize = 6),show_heatmap_legend = TRUE,
+                        column_title_gp = grid::gpar(fontsize = 6, fontface = "bold"),col = CNV_col,width = grid::unit(CNVwidth, "cm"),heatmap_legend_param = list(title_gp = grid::gpar(fontsize = 8),labels_gp = grid::gpar(fontsize = 6)))
+      ha_list<-ha_CNV + ha_list
+    }
+  }
+
+  if (!is.null(SAMPLE_annotation)){
+    if (ID %in% colnames(SAMPLE_annotation)){
+      SAMPLE_annotation_fil<-as.data.frame(SAMPLE_annotation) %>% dplyr::filter(!!as.name(ID) %in% overlapping_samples_clust)
+      suppressWarnings(SAMPLE_annotation_fil<-dplyr::left_join(as.data.frame(overlapping_samples_clust),SAMPLE_annotation_fil,by=c("overlapping_samples_clust"=ID)))
+      SAMPLE_annotation_fil<-tibble::column_to_rownames(SAMPLE_annotation_fil,"overlapping_samples_clust")
+      cat(nrow(SAMPLE_annotation_fil),"samples have an annotation.\n")
+      cat(ncol(SAMPLE_annotation_fil),"annotations are added")
+      #define colors
+      col<-c()
+      for (sample_column in colnames(SAMPLE_annotation_fil)[colnames(SAMPLE_annotation_fil) != ID]){
+        newcol<-circlize::rand_color(n=length(unique(SAMPLE_annotation_fil[,sample_column])),luminosity = "bright")
+        names(newcol)<-unique(SAMPLE_annotation_fil[,sample_column])
+        col<-c(col,newcol)
+      }
+      ha_anot<-Heatmap(SAMPLE_annotation_fil, name="Sample Annotation", column_title = "Sample\nAnnotation", column_title_gp = grid::gpar(fontsize = 6, fontface = "bold"), col=col, show_row_names=FALSE,width = unit(ncol(SAMPLE_annotation_fil) * 2, "mm"),
+                       column_names_gp = gpar(fontsize = 6),heatmap_legend_param = list(title_gp = grid::gpar(fontsize = 8),labels_gp = grid::gpar(fontsize = 6)))
+      ha_list<-ha_list + ha_anot
+    } else {print("The ID is not identified as a column name in the annotation")}
+  }
+  ComplexHeatmap::draw(ha_list,heatmap_legend_side = "bottom",annotation_legend_side="bottom")
+}